A large-sample investigation of statistical procedures for radar-based short-term quantitative precipitation forecasting

Grecu, Mircea; Krajewski, Witold F.

doi:10.1016/s0022-1694(00)00360-7

Cited by 82 publications

(96 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Hence, extrapolationbased nowcasting algorithms using existing remote-sensing information have been used extensively, especially within the first few hours of the occurrence of storm events (Grecu and Krajewski, 2000;Montanari et al 2006).…”

Section: Sqpf With Extrapolation-based Modelsmentioning

confidence: 99%

“…A general representation of the extrapolation-based nowcasting system is described below (Grecu and Krajewski, 2000;Laroche and Zawadzki, 1995;Montanari et al, 2006):…”

Section: Sqpf With Extrapolation-based Modelsmentioning

confidence: 99%

“…The storm variation is a result of the advection vectors of U x , V y . In addition, the function g represents a dynamical Lagrangian process in which a future storm's intensity is a result of its historical changes in a Lagrangian reference frame that travels along the storm path (Grecu and Krajewski, 2000). Considering a storm in the smallest possible unit (pixels), Eq.…”

Section: Sqpf With Extrapolation-based Modelsmentioning

confidence: 99%

“…Some investigators have proposed approaches to track and forecast thunderstorms with the highest possible resolution (Eq. (1): spatial resolution in the scale of each pixel) (Tuttle and Foote, 1990;Grecu and Krajewski, 2000;Germann and Zawadzki, 2002;Ridal et al, 2010). Two particular classes of algorithms have been used to estimate storm velocity from two consecutive images.…”

Section: Sqpf With Extrapolation-based Modelsmentioning

confidence: 99%

See 3 more Smart Citations

Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach

Zahraei

Hsu

Sorooshian

et al. 2012

Atmospheric Research

View full text Add to dashboard Cite

show abstract

Section: Sqpf With Extrapolation-based Modelsmentioning

confidence: 99%

“…A general representation of the extrapolation-based nowcasting system is described below (Grecu and Krajewski, 2000;Laroche and Zawadzki, 1995;Montanari et al, 2006):…”

Section: Sqpf With Extrapolation-based Modelsmentioning

confidence: 99%

Section: Sqpf With Extrapolation-based Modelsmentioning

confidence: 99%

Section: Sqpf With Extrapolation-based Modelsmentioning

confidence: 99%

See 2 more Smart Citations

Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach

Zahraei

Hsu

Sorooshian

et al. 2012

Atmospheric Research

View full text Add to dashboard Cite

show abstract

“…This implies that similar features are observed in precipitation fields on a continuum of spatial scales from the very small (centimetres) to the very large (thousands of kilometres). Furthermore, it has been shown that the lifetime of precipitation features is broadly proportional to their size Grecu and Krajewski, 2000;Germann and Zawadzki, 2002). Thus, the smallest features observed by operational weather radar may persist for no more than a matter of minutes, while the largest features may persist for many hours or even days.…”

Section: Introduction: the Limitations Of Conventional Short-range mentioning

confidence: 99%

Use of a stochastic precipitation nowcast scheme for fluvial flood forecasting and warning

Pierce

Bowler

Seed

et al. 2005

Atmospheric Science Letters

View full text Add to dashboard Cite

In collaboration with the Bureau of Meteorology (Melbourne, Australia), the Met Office (Joint Centre for Hydro-Meteorological Research, UK) has developed a stochastic precipitation nowcast scheme, designed to model and predict the PDF of surface rain rate and rain accumulation in space and time. Here we demonstrate the range of probabilistic products generated by the scheme, and their potential applications for fluvial flood forecasting and warning.With the aid of a hydrological model (the PDM), we consider the use of ensembles of predicted catchment rain accumulation in evaluating the range of possible river flow responses from a given catchment. When employed in conjunction with a catchment specific, cost-based decision-making model, we highlight the value of PDFs of forecast catchment rainfall accumulation and river flow as an aid to objective decision making within the flood warning process.  Crown

show abstract

The Cloud Top Distribution and Diurnal Variation of Clouds Over East Asia: Preliminary Results From Advanced Himawari Imager

et al. 2018

View full text Add to dashboard Cite

Clouds, as one of the most uncertain factors in climate system, have been intensively studied as satellites with advanced instruments emerged in recent years. However, few studies examine the vertical distributions of cloud top and their temporal variations over East Asia based on geostationary satellite data. In this study, the vertical structures of cloud top and its diurnal variations in summer of 2016 are analyzed using the Advanced Himawari Imager/Himawari‐8 cloud products. Results show that clouds occur most frequently over the southern Tibetan Plateau and the Bay of Bengal. We find a steep gradient of cloud occurrence frequency extending from southwest to northeast China and low‐value centers over the eastern Pacific and the Inner Mongolia Plateau. The vertical structures of cloud top are highly dependent on latitude, in addition to the nonnegligible roles of both terrain and land‐sea thermal contrast. In terms of the diurnal cycle, clouds tend to occur more often in the afternoon, peaking around 1700 local time over land and ocean. The amplitude of cloud diurnal variation over ocean is much smaller than that over land, and complex terrain tends to be linked to larger amplitude. In vertical, the diurnal cycle of cloud frequency exhibits bimodal pattern over both land and ocean. The high‐level peaks occur at almost the same altitude over land and ocean. In contrast, the low‐level peaks over ocean mainly reside in the boundary layer, much lower than those over land, which could be indicative of the frequent occurrence of marine boundary layer clouds.

show abstract

A large-sample investigation of statistical procedures for radar-based short-term quantitative precipitation forecasting

Cited by 82 publications

References 25 publications

Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach

Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach

Use of a stochastic precipitation nowcast scheme for fluvial flood forecasting and warning

The Cloud Top Distribution and Diurnal Variation of Clouds Over East Asia: Preliminary Results From Advanced Himawari Imager

Contact Info

Product

Resources

About